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Risk of landscape failure examined through big data analysis; implications of Oil Sand mine closure planning

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  • Full or part time
    Dr N Kettridge
    Prof D M Hannah
  • Application Deadline
    No more applications being accepted
  • Competition Funded PhD Project (European/UK Students Only)
    Competition Funded PhD Project (European/UK Students Only)

Project Description

The reconstruction of the Alberta oil sands represents one of the largest restoration challenges on the planet. Such constructed landscapes must be designed to develop rapidly over time, producing expansive productive forests that maximize the economic potential of the landscape and maintain high water fluxes to flush ecologically harmful salts. At the same time, the landscape design must limit the risk of failure, forming resilient environments which follow planned trajectories within the dry sub-humid climate of the Western Boreal. This research project integrates sound mathematical and statistical analysis of big data to identify the sources of such risk, their drivers and impacts within these complex boreal systems.

A system dynamics model informed from current process based understanding will be developed representing hydrological stores and transfers within the Western Boreal Plain. These landscapes have formed the focus of close to two decades of research by the project partners; legacy data which is being compiled into a readily available data rich achieve (measurements from ~15000 wells in addition to a range of supplementary hydrological, meteorological and ecological data). The models will be optimised and evaluated against this hydrological data. The modelling approach will be developed within STELLA, an intuitive icon-based graphical interface that enables detailed exploration and development of system dynamics. It will offer the opportunity to develop multi-level, hierarchical model structures that can serve as building blocks for large complex systems. The top down approach will enable key leverage points to be identified and the analysis of different system organisations and structures. The modelling framework will be applied to explore how the climate cycle, a superposition of varying climate signals of different intensities and phases, provides the overarching driver of the ecohydrology behaviour of these landscape. Further, how this climate cycle cascades through landscape storage units that vary in configuration, extent and scale of connectivity. It will determine how such complex interactions trigger periods of water scarcity over varying spatial and temporal scales that place individual ecosystem at risk of failure. The project will identify how such collapses and the resultant shift in hydrological function result in a loss of system resilience that may cascade through the landscape leading to its potential large scale failure.

In addition to training opportunities provided by the DREAM DTC, you will integrate within the Water Science group and Birmingham Institute of Forest Research (BIFoR). You will also join a core team of researchers within the Hydrology Ecology and Disturbance (HEAD3) project funded in partnership by industrial partners Syncrude and Canadian Natural Resource Ltd. This consortium composes of the University of Birmingham, University of Alberta, McMaster University and University of Waterloo.

About you: Applicants should hold a minimum of an Honours Degree at 2:1 level or equivalent in subjects such as Environmental Science, Computer Science, Mathematics, Statistics, Engineering, Geography or Natural Sciences.

For further details: Please contact Dr Nick Kettridge:

Funding Notes

Fully funded DREAM (NERC) project

How good is research at University of Birmingham in Geography, Environmental Studies and Archaeology?

FTE Category A staff submitted: 25.00

Research output data provided by the Research Excellence Framework (REF)

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